Enkata Updates Architecture for Big Data

Friday Jan 20th 2012 by Ann All

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The provider of cloud-based customer experience analytics and workforce optimization software is using Hadoop and other emerging technologies to help its clients enjoy business intelligence benefits from Big Data.

Enkata, a provider of cloud-based customer experience analytics and workforce optimization solutions, is seeing the needs of its customers with contact centers begin to shift. Like other companies that log lots of customer transactions, many Enkata clients are experiencing an “explosion” of data, an increasing amount of it coming from less traditional sources like video, explained Alex Delarue, Enkata’s chief technology officer.

That is why Enkata is tweaking its architecture to make it better able to handle so-called Big Data, large volumes of structured and unstructured data originating from a wide variety of sources, including transaction logs, interactive voice response (IVR) systems, the Web and agent desktop activity.

Like a growing number of companies, Enkata is using Hadoop as well as other Big Data technologies to help its clients handle their data more efficiently and, more important, get data into the hands of analysts more quickly.

“We are using a combination of technologies to bring data to the end user as soon as possible,” Delarue said. “We also want to offer more flexibility to the analyst community so they can inject their own data and derive insights without worrying too much about schema design and things like that.”

Delarue said Enkata is planning a more innovative approach than simply creating connectors between Big Data and traditional SQL databases, the technique he said is employed by many business intelligence providers that offer Big Data solutions. “It should not be just about handling a lot more data more efficiently, but being able to shrink the time between data capture and business intelligence,” he said.